Implement AI with a Trusted Agency

Don't gamble on AI. Work with a proven AI solutions partner that will accelerate time to market. We've developed  a proven framework that’s been tested by startups and billion dollar companies alike.
Trusted By
why us

We Build Custom Large Language Models Based on Your Data, Brand and Beliefs.

The best LLMs use an organization's data to act like another employee. Our team of AI consultants create a strategy to build a trusted platform that only outputs approved content and tasks. From having AI respond to social comments to doing repetitive tasks, we make sure you LLM will be cost-effective, fast, and accurate with responses.

Understand the Potential for AI for Your Business - Booking Fast

We are booking up for 2024 already, contact us now to book one of the open slots.

Work with an AI Agency that's been Launching Solutions Since 2017.

We’ve  aleady published 7 generative AI apps and are already working on more. With NineTwoThree, you’ll have a team that’s on the edge of innovation and has poured significant resources into testing AI tools to better help our clients.
Vendor Agnostic
We’re not tied to any providers. We’ll only recommend AI services & tech that’s right for your business.
Industry Agnostic
We've been in business for over 12 years and have worked across most industries.
In-House Skills
We have a team of data scientists, researchers, and engineers  who have launched AI projects successfully.
AI Solutions with ROI
We customize solutions for every business and calculate ROI. We build for long-term impact.

Superior Screening


Superior Screening

Build a semantic search engine that interviews candidates using trained models to determine qualifications and culture fit.
Build a semantic search engine that interviews candidates using trained models to determine qualifications and culture fit.

Rapid Reasoning


Rapid Reasoning

Teach AI how to mimic human reasoning, analyze scenarios, weigh options, and make logical decisions – just like a human brain.
Teach AI how to mimic human reasoning, analyze scenarios, weigh options, and make logical decisions – just like a human brain.

Supercharge Sales

Supercharge Sales

Supercharge Sales

Supercharge SalesSupercharge Sales
Automatically qualify and prioritize leads by scoring inbound leads based on past customer behavior and engagement.
Supercharge Sales
Supercharge Sales
Supercharge Sales
Automatically qualify and prioritize leads by scoring inbound leads based on past customer behavior and engagement.

Coding Co-Pilots

Coding Co-Pilots

Coding Co-Pilots

Coding Co-PilotsCoding Co-Pilots
From creating solutions to translating languages, get a co-pilot that generates code for  repetitive tasks.
Coding Co-Pilots
Coding Co-Pilots
Coding Co-Pilots
From creating solutions to translating languages, get a co-pilot that generates code for  repetitive tasks.

Customer Champions

Customer Champions

Customer Champions

Customer Championscustomer-chapmpions
Your bots can respond to inquiries, provide information and pass conversations to your team when they need more detailed responses.
Customer Champions
Your bots can respond to inquiries, provide information and pass conversations to your team when they need more detailed responses.

Savvy Social Responses


Savvy Social Responses

Respond to social media comments with on-brand information so comments are quickly answered with approved messaging.
Respond to social media comments with on-brand information so comments are quickly answered with approved messaging.

Successful AI Solutions


Prisonology Transforms Legal Advocacy with AI

NineTwoThree used Large Language Models (LLMs) and Retrieval-Augmented Generation to automate the Security Designation Scorecard.


SWEE Increased Downloads by 304%

SWEE helps golfers improve their swings by taking a video of each hole and using AI to give feedback. Our mobile apps team relaunched the business by revamping the user experience and making it easier for caddies to connect cameras on the golf course to the iOS app.


Improving Patient Monitoring With IoT And AI

Life Detection Technologies (LDT) leverages AI and wireless sensors to make its medical devices either and more comfortable to use. NineTwoThree created data pipelines for its sensors and developed intuitive dashboards so healthcare professionals can better track patient health.


Driving Transactions with a Custom Machine Learning Algorithm

Cymbiotika upgraded their online shopping experience using a machine learning recommendations system. NineTwoThree used their data to create product personalization that increases customer  engagement and sales.


We helped Dataflik MRR grow 634% to $2.5M in 12 months

Dataflik helps real estate investors improve their business marketing operations. NineTwoThree built the machine learning model that generates prioritized lists of motivated sellers faster and more accurately than a human expert.


An Award Winning Software Design, Engineering & Marketing Studio

We help established brands iterate like startups and startups scale like established brands. Partnering with industry leaders and visionary entrepreneurs we focus on profit producing applications that are a delight to use. We leverage this transformation through the power of agile methodology, design thinking and impeccable engineering to help our clients rapidly identify and validate new products. And we have the stats to back it up...







Years in business


Boston Agency


Years in a row

Tyrus Garrett, CEO of Dataflik

Thanks to the algorithm that NineTwoThree Studio has helped us construct, we predict accurately about 60%–70% of home sales. We’re one of the top five companies in the industry. We’re pretty happy with that, and it gets better every month.


Get Predictive Super Powers

You might not need to predict traffic, suggest shows or match lovers.
But we’re sure you want to use computers + data to improve your business.
Your business is unique. Your web and mobile apps should be too. That’s why we build everything from scratch, every time.
Your needs can change based on the market. We grow or shrink with you because your needs are our priority.
We meet weekly and give you access to our tools so you always know what’s going on with your app.
We’ve been doing this for so long that we know exactly what it takes. Our last 27 projects finished 7% within budget.
We are the best because we hire the best and all of our developers have been on the team for over a year.
We get it right the first time so you can forecast the future and meet your goals.

Meet Your Data Scientists

data scientist


Senior level solution architect with a vast history of Machine Learning projects. Most notably, Oleksandr implemented a model that allows EV station owners to predict which stations were available to charge the vehicles. This was a massive undertaking that operates the largest EV market in Europe.
8 Years Experience with NineTwoThree

AWS Certified Solutions Architect
Machine Learning with TensorFlow Google Certified
Google Data Analytics Professional Certificate
AWS Certified Clout Practitioner
Master in Computer Science, with MBA
data scientist


Senior Level Data Scientists with world renowned results for NLP models in both the Human Resource hiring process for a major USA company and replicating therapists - scoring equivalent to humans using GPT. Also supported the EV charger station project for the US market.

4 Years Experience with NineTwoThree
Machine Learning Neural Networks Certificate
• Improving Deep Neural Networks Certificate
• Convolutional Neural Networks Certificate
• Natural Language Processing with Vectors Spaces (
• Statistical Inference from John Hopkins University
data scientist


Skilled Data Scientist with 4-years experience in computer vision, clustering analysis, object detection and tabular data classification. Also well acquainted with classification, decision trees, data pre-processing, cleaning, as well as neural networks.

4 Years Experience with NineTwoThree
MLOps Professional Training Program
• AWS Cloud Practitioner
• Computer Vision and Artificial Intelligence from Abto
• Natural Language Processing with Vectors Spaces (
• Statistical Inference from John Hopkins University
data scientist


Skilled Data Scientist with experience in computer vision, clustering analysis, object detection and tabular data classification. Built out a prediction model for 3d CT scans to predict the lungs capacity to detect pulmonary fibrosis for a major medical research company in Sweden.

2 Years Experience with NineTwoThree
Deep Learning DeepMind Certified Course
• CNN DeepMind Course Certification

Accelerated AI Innovation Playbook


Build the Prototype

Start Simple: Initially, the setup involves a direct interaction between your application and the API.

Prototype Importance: It's easy to create a cool prototype with the models, but transitioning to production is more complex due to the models' non-deterministic nature.

Develop a User-Centric Experience

Human-Centric Design: Focus on building applications that enhance and augment human capabilities, not replace them.

Managing Uncertainty: Optimize user experience by managing model interactions and responses.

UX Elements: Incorporate elements like suggestive prompts, feedback controls, and AI notices to guide users and manage inherent uncertainty.
Enhancing Model Consistency

Enhancing Model Consistency

Grounding with External Knowledge:
  • Utilize Knowledge Stores: Link the AI model to real-world information to minimize hallucinations.
  • Retrieval Services and Databases: Leverage these tools for providing context-specific data to the AI model.
Model Behavior Constraints:
  • JSON Mode: Ensure outputs adhere to the JSON format for system compatibility.
  • Reproducible Outputs: Introduce parameters for consistent AI responses.
Evaluating and Iterating

Evaluating and Iterating

Building Evaluation Suites: Develop tailored evaluations to measure the model's performance in real-world scenarios.

Automated Evals: Implement AI-driven evaluations to supplement human judgment and efficiently handle repetitive tasks.

Model-Graded Evals: Use the AI model itself to assess and compare responses, optimizing for accuracy and relevance.

Scalability and Cost Management

Semantic Caching: Implement a system to store and reuse responses for similar queries, reducing reliance on real-time API calls.
Model Routing Strategies:
  • Cheaper Model Alternatives: Substitute expensive models with more cost-effective versions without compromising quality.
  • Fine-Tuning for Specific Use Cases: Customize more affordable models to meet specific application needs.

Large Language Model Operations

Operational Management Framework: Establish a comprehensive system for managing LLMs, covering all aspects from development to deployment.
Key Capabilities:
  • Performance Optimization: Continuously monitor and improve model performance.
  • Security and Compliance: Ensure the application adheres to relevant standards and regulations.
  • Data and Embedding Management: Effectively handle the data processed and generated by the AI models.
  • Development Velocity: Accelerate the development process while maintaining quality.
Observability and Troubleshooting: Implement tools for in-depth analysis and quick resolution of issues in production.
Future Outlook and Continuous Development

Future Outlook and Continuous Development

Evolving Landscape: Acknowledge the dynamic nature of AI development and the need for ongoing adaptation and learning.
Collaboration and Community: Emphasize the role of collective efforts in advancing the field of AI application development.

How Can Artificial Intelligence and Machine Learning Apps Transform Businesses?

Machine learning and artificial intelligence have already established themselves as powerful tools for businesses to harness in their search for efficiency, cost-reduction, and improved operations. 

By relying on these high-tech solutions in the form of applications suitable for everything from early-stage startups to mass enterprises, machine learning is quickly becoming a vital part of the world of business. But how and why these technologies, and is it possible to use them in any industry?

Many companies are data and process-heavy but still rely on traditional methods of managing them. With artificial intelligence apps built by expert agencies housing master machine learning engineers, several industries are already being transformed, from supply chain management to healthcare, eCommerce, and education to name just a few.

These technologies are helping real-world businesses better understand customer data, automate tedious processes, and have the added benefit of iterating as they scale. That means that if you choose artificial intelligence technology as a solution for your business, it will grow with you.

What is Artificial Intelligence vs Machine Learning?

Machine learning is as the name implies ultimately a learning process. In essence, code is used to create an algorithm that can extract information from labeled or unlabelled data. What makes machine learning techniques different from other types of algorithm models is that the code is made to adapt and change as it gains more information. 

This foundation helps the application identify and analyze patterns, make behavioral predictions or take on other intended goals.

There are also different types of machine learning tools and these different categories have distinct purposes. We discuss artificial intelligence and the key differences in our FAQs below.

What Are The Different Types Of Machine Learning?

Machine learning as a solution is usually divided into four categories: supervised, semi-supervised, unsupervised, and reinforcement learning.

Supervised learning refers to a machine learning algorithm that is manually taught information. Much like a child learning in school, the application is given known datasets and told the desired outcome. Then it’s up to the supervised machine learning algorithm to arrive at the intended destination.

Semi-supervised machine learning solutions are rather similar to supervised learning ones, except the data provided for the algorithm is a mix of known and unknown data sets. The goal here is to teach the algorithm to understand the known data and then to use that as a basis from which to label or categorize the unknown data.

Then there is unsupervised learning. This is the wild west of machine learning, where the algorithm is left to study and interpret large data sets without any input or supervision. The idea here is that the machine learning app will find a way to categorize the data into some sort of structure.

And last but not least there is reinforcement learning. Here, the algorithm is given a set of actions, requirements, limitations, and the expected final values. The machine learning solution tries to achieve the end result through various methods in order to find the most efficient one. The app is allowed to learn through trial and error, which iteratively helps it get to the best end result.

For the difference between machine learning algorithms and machine learning models, check out this post.

How are Machine Learning Algorithms Used In Machine Learning Projects?

Machine learning and artificial intelligence both already have existing footprints in the business world, from smaller companies to some of the largest enterprises around the globe. In fact, different types of AI and supervised learning algorithms are already used to customize experiences on smartphones, web browsers, and other online platforms.

From Tesla’s machine learning models for their autopilot modes to social media platforms adapting to show users content they might like, there is machine learning in more applications today than ever before.

Streaming giant Netflix is said to have saved as much as $1 billion due to its machine learning algorithm for content recommendations,  while Google and other search engines commonly use machine learning to improve their search results, maps, and language translation capabilities.
And they aren’t the only ones - companies like Salesforce and Hubspot use it to enable user automation that improves marketing flows.

Why is Machine Learning Mastery Essential for Businesses?

Machine learning is an incredible tool because it is both flexible and adaptable. This type of technology can be applied to any industry, and all industries can enjoy the benefits of improved efficiency, data-tracking, cost reductions, and much more.

What makes these algorithms even more powerful is that they can go from as simple as tracking sales or social media performance to complex solutions for language or audio recognition.

The most important thing to know about machine learning for businesses is that it is vital to work with a machine learning agency that has a proven track record in delivering machine learning and AI solutions for various industries. Choosing the wrong machine learning partner can be highly detrimental and end up costing businesses thousands of dollars in wasted time and effort.

NineTwoThree Venture Studio is an experienced machine learning agency most recently honored for the second time by Inc. 5000 and having been ranked as the top development and mobile app development company in Boston by Let us organize your data to make better decisions or build Machine Learning and AI software to improve your business.

We're always thinking about Generative AI

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